實體零售商店運用LRFM模型探討顧客價值之研究

在現今大數據時代崛起的洪流中，企業必須朝著利用各種銷售資料的數據去分析並深入研究網購者對眾多網路銷售平台消費者的特性、喜好、意願還有所重視的購買決策因素。如何利用創新思維，顛覆購物體驗成為了最重要的成敗關鍵，近年來「以消費者為中心的數據驅動」為核心的新零售發展，結合大數據和雲端科技進行金種行銷，不僅僅為數位行銷產業，也替實體行銷產業帶來了變革與創新應用。本研究探討了疫情期間數位化趨勢對台灣傳統中小企業的影響，並提出利用數據驅動的行銷策略應對市場變化。透過應用RFM模型及其改進的LRFM模型，再使用Power BI和SPSS等工具對某中小企業零售商的顧客交易資料進行分析。將交易筆數7,535筆交易紀錄，進行歸戶轉成6,552位顧客資料，進行後續分析。再通過LRFM指標結合分群分析技術對顧客進行分群，並利用購物籃分析找出各群顧客購買商品的關聯，進一步推展客製化的行銷活動，以提升顧客保留率和預測顧客生命週期。由本研究結論得知不同顧客群體在購買頻率、金額、最近購買時間和顧客關係長度上存在顯著差異。依據這些差異，將顧客分為「冠軍型」、「忠誠型」、「有潛力型」、「潛在忠誠型」、「新客戶」、「不可失去型」、「即將沉睡型」、「休眠型」、「風險型」及「失去型」等十個類型。再進一步利用購物籃分析找出商品之間的關聯性，發現「日本食品類」是各類客群共同的主要購買品項，並提出針對不同顧客類型的行銷策略，如VIP獎勵制度、促銷資訊推廣、產品頁面影片內容等。

關鍵字

RFM模型；關聯準則；消費者特性；購物週期；顧客分群

並列摘要

In the era of rising of data,cooperates have to utilize all kinds of sales data to analyze the consumer behaviors of online shoppers’ characteristics, preferences and wills and value the factors of making decisions. How to use innovative mindset to overthrow shopping experiences has become a key to success. The development of retailing and the core of customer-based data combined with big data and cloud technology recently brings revolution and innovation to the new digital marketing industry. This research discusses the effect of digitalization of Taiwanese SMEs during pandemic and addresses using data-driven marketing strategies to deal with changes of the market. Via using the RFM model and LRFM model with the use of Power BI and SPSS and so on to analyze the trading data form a small-medium sized retailer. Using 6,552 customers data out of 7,535 records via LRFM index categorizes customers into groups and use shopping cart analysis to find out the connection of products bought by customers and further promote customization marketing strategies for customer retention and prediction of life cycle of consumers. It is known by the research that the differences of different groups of customers from buying frequencies, amounts of money spent, recent buying times and customer loyalty are obvious. Customers have been categorized into 10 groups from the differences which are「Champions」、「Loyal」、「Promising」、「Potential Loyalist」、「New Customers」、「Cannot Lose Them」、「About To Sleep」、「Hibernating Customers」、「At Risk」、「Lost Customers」。 by using shopping cart catagorization, it is found that most of the customers will buy Japanese snacks even though they belong to different categories, and also brings up different marketing strategies to different categories, such as VIP rewards, information of promotions, videos of products and so on.